Data Link Layer Research Articles

Error rate detection due to primary user emulation attack in cognitive radio networks

Security threat is a crucial issue in cognitive radio network (CRN). These threats come from physical layer, data link layer, network layer, transport layer, and application layer. Hence, security system to all layers in CRN has a responsibility to protect the communication between among Secondary User (SU) or to maintain valid detection to the presence of Primary User (PU) signals. Primary User Emulation Attack (PUEA) is a threat on physical layer where malicious user emulates PU signal. This paper studies the effect of exclusive region of PUEA in CRN. We take two setting of exclusive distances, 30m and 50m, where this radius of area is free of malicious users. Probability of false alarm (Pf) and miss detection (Pm) are used to evaluate the performances. The result shows that increasing distance of exclusive region may decrease Pf and Pm.

A New Transmission Control Application Protocol Optimization Method Based on PROFIBUS-DP

This paper presents an optimization solution on PROFIBUS-DP bus protocol with Ethernet technology. This plan can meet the demands of higher speed and higher reliability of transmission control protocol inside enterprises. It sets up DP Ethernet by defining physical layer, data link layer protocol and establishing EDDL function. The new constructed protocol named DP Ethernet is compatible with the applications based on upper PROFIBUS-DP protocols. It also can support much wider communication bandwidth. DP Ethernet protocol is more efficient than PROFIBUS-DP through analysis on message cycle time and message coding efficiency of networks based on these two protocols.

An AUV-Aided Cross-Layer Mobile Data Gathering Protocol for Underwater Sensor Networks.

Underwater sensor networks (UWSNs) have recently attracted much attention due to their ability to discover and monitor the aquatic environment. However, acoustic communication has posed some significant challenges, such as high propagation delay, low available bandwidth, and high bit error rate. Therefore, proposing a cross-layer protocol is of high importance to the field to integrate different communication functionalities (i.e, an interaction between data link layer and network layer) to interact in a more reliable and flexible manner to overcome the consequences of applying acoustic signals. In this paper, a novel Cross-Layer Mobile Data gathering (CLMD) scheme for Underwater Sensor Networks (UWSNs) is presented to improve the performance by providing the interaction between the MAC and routing layers. In CLMD, an Autonomous Underwater Vehicle (AUV) is used to periodically visit a group of clusters which are responsible for data collection from members. The communications are managed by using a distributed cross-layer solution to enhance network performance in terms of packet delivery and energy saving. The cluster heads are replaced with other candidate members at the end of each operational phase to prolong the network lifetime. The effectiveness of CLMD is verified through an extensive simulation study which reveals the performance improvement in the energy-saving, network lifetime, and packet delivery ratio with varying number of nodes. The effects of MAC protocols are also studied by studying the network performance under various MAC protocols in terms of packet delivery ratio, goodput, and energy consumption with varying density of nodes.

Optimizing network lifetime and QoS in 6LoWPANs using deep neural networks

Internet Protocol version 6 (IPv6) over low power wireless personal area networks (6LoWPANs) forms a majority of traffic share in Internet of things (IoT) where quality of service (QoS) becomes obligatory for multitude of sensor inputs. 6LoWPANs are interference prone due to the fact that the data link and physical layers utilize the IEEE 802.15.4 standard for communication. Interference in 6LoWPANs results in poor QoS in terms of packet reception ratios and packet loss rates and also in poor network stability and reduced network lifetime. A deep neural network based routing algorithm is proposed which offers multiple solutions to the interference problem and selects the best solution in order to reduce interference. The proposed routing algorithm improves the network lifetime, delay and jitter on an average by 50%, 40%, and 25% respectively compared to the standard 6LoWPAN routing protocol. The signal to interference and noise ratio is also improved on an average by 18 decibel.

A novel multi-objective optimizer framework for TDMA-based medium access control in IoT

Recently, cross-layer optimization has been emphasized by researchers for Internet of Things (IoT) where billions of devices communicate intelligently making every day communication highly informative. Medium Access Control (MAC) sub-layer is part of data link layer in IoT protocol stack. The energy consumption of things is greatly affected by MAC protocol which controls the node radio functionalities. In this article, we propose the design of an efficient MAC for IoT by minimizing its energy consumption at various levels. The minimization model is subject to reduction in distortion levels while simultaneously extending network lifetime. This article synthesizes and optimizes MAC layer of IoT based protocols using a novel delta diagram synthesizer and accurately captures both the high heterogeneity of the IoT and the impact of the Internet as part of the MAC layer architecture. Furthermore a novel hybrid Whale-Artificial Bee Colony optimizer framework is proposed to obtain optimal nodes based on energy consumption and the communication parameters among things, by exploiting the interrelations among different layer functionalities in the IoT. This novel system saves considerable computation resources of the resource constrained IoT devices and adapts to various data sources with different distortion levels rapidly.

Improvement of Network Cyber Security Services using Security Operation Models

Concerns for service computer networks’ security and reliability are growing rapidly due to increasing service devices with connections to external networks. This aggravates vulnerability of service networks to cyber attacks through external connections. Though encryption can provide security for user data transmissions, encryption itself could not provide protections against traffic analysis attacks. Techniques against traffic-analysis attacks through statistically controlling the transmission rate of padded and encrypted frames are unsuited for power system applications. This paper proposes three security operation modes for the newly developed security layer, located below DNP3 data-link layer, to strengthen encryption and authentication operations against the effectiveness of traffic- analysis and cryptanalysis attacks. The security models use padding to disguise the amount of user data transmitted and disguise the user data link layer frame amongst a group of manufactured frames similar to statistically controlling data transmission rate. The proposed security operations have been successfully applied to enhance power system security controls.

Link State Machine of PCI Express

PCI Express is a high-speed serial computer expansion bus standard with advance error reporting technology. It is the common motherboard interface for personal computers' graphics cards, hard drives, SSDs, Wi-Fi and Ethernet hardware connections. A link in PCIe is the communication path between transmitter and receiver. PCIe operates in all transaction, data link and physical layer. The link bring up in physical layer is essential for the link state machine to proceed further into data transfer state. This paper analyses the Link training and status state machine for the Detect, Polling, Configuration and Recovery states. The state analysis is simulated using the TS1 and TS2 packets transfer between Root Complex and End Point.

Adaptive structure modeling and prediction for swarm unmanned system

In recent years, swarm unmanned systems (SUSs) have become crucial in the military field, both at home and abroad. This has promoted the evolution of the unmanned combat mode from single-platform remote-control to intelligent-swarm combat. SUSs support the cooperative, autonomous, and flexible characteristics of the combat system under uncertain tasks and environments. The overall swarm performance depends on the system and structure among its members and also dynamically evolves with the time and the environment. Thus, new intelligence emerges from the interaction among systems. Starting from the evolution of the SUS structure, this paper proposes the model of a three-layer structure and a relationship involving the data-link layer, the SUS, and the task requirements. The multidimensional spatial relationship model is transformed into a two-dimensional graphical representation model by using a graph neural network; then, the dependency graph of the relationships of the systems and layers of the SUS is constructed. The integral network is classified according to a task-based standard. The recursive neural network algorithm is derived from the intra- and interlayer relationships. The SUS structure is predicted via some examples of training data sets and the attribute labels of task-based nodes. The impact of the system or data layer damage can be evaluated according to the weight parameters of the structure dependence relationship. Finally, the autonomous decision of the SUS from the task to the swarm structure is realized.

A Novel Security Protocol for Wireless Sensor Networks with Cooperative Communication

This paper builds upon the foundation and clarifies specifications for a necessary security protocol in Wireless Sensor Networks (WSNs) with cooperative communications. It is designed to enhance performance and resiliency against cyber-attacks. Recent literature has shown that developing a WSN with Cooperative Communication greatly increases the performance of the network, but also exposes new vulnerabilities. The technique operates by transmitting packets of data to neighboring relay nodes in a cooperative fashion to reach the destination. In this paper, we consider security issues in WSNs with cooperative communication on each layer of the OSI model: physical layer, data link layer, network layer, service (topology) layer, and application layer. For each layer, we clarify the main task, enumerate the main attacks and threats, specify the primary security approaches and techniques (if any), and discuss possible new attacks and problems that may arise with the use of cooperative communications. Furthermore, we show for some attacks (e.g., jamming, packet dropping, and wormhole) that using cooperative communication improves the network resiliency and reliability. Finally, we propose a security protocol that addresses many of these shortcomings, while outlining the remaining issues that need further work and research.

A Multipath Packet Scheduling Approach based on Buffer Acknowledgement for Congestion Control

Abstract Congestion is an important concern in both wired and wireless communication systems. Several technologies are in use for the data link, network, and transport layer to manage congestion. Conventional congestion control approaches are unreliable for transport layer protocols by means of congestion control mechanisms utilized for multimedia streaming. Packets that schedule flow control to employ multiple network interfaces to smoothly transmit streaming data play an important role in congestion control by overwhelming the intermediate node’s buffer and causing packet loss. In this paper, we propose a Multipath Packet Scheduling (MP-PS) approach to efficiently stream the data packets in multiple paths. It consists of a Multi-Path Packet Scheduler (MPS) to perform the path scheduling based on the path scheduling delay probability, and a Multipath Congestion Control (MCC) to regulate the congestion control through an explicit acknowledgment for the rate of transmission control based on packet delivery rate and buffer availability. It aims to reduce packet loss and improve the throughput utilizing the MP-PS approach. The proposed approach has been extensively simulated by means of a simulator and it showed improvised performance in provisions of throughput and buffer utilization when evaluated with the conventional approach.

Transient Error Correction Coding Scheme for Reliable Low Power Data Link Layer in NoC

Ensuring reliable data transmission in multicore System on Chip (SoC), which employs Network on Chip (NoC), is a challenging task. This task is well addressed by Error Correcting Codes (ECC) in on-chip as well as off-chip networks. ECC significantly improves reliability of NoC interconnects with area and power overhead. In this paper, we propose a novel Transient Error Correction (TEC) coding scheme for reliable low power data link layer in NoC to attain a high error correction capability with less hardware overhead. Performance of TEC scheme is evaluated with realistic traffic patterns and validated with simulation results. The proposed scheme has less residual errors than the Hamming product code enabling reliable transmission at lower link swing voltage. Further, the scheme reduces the power consumption of NoC interconnects up to 71% as compared to Hamming product code with a marginal increase in codec delay and thus router delay. TEC scheme performs well in high noise environment with no delay penalty associated with retransmission.

Towards Quantum Satellite Internetworking: A Software-Defined Networking Perspective

Recently, quantum computing and communications rapidly developed to interconnect heterogeneous quantum devices. In particular, some researchers have been performed about terrestrial quantum communications over typical optical fiber links. However, this technology is affected by extremely high losses that can be faced only through the deployment of several repeaters, which in turn involve impractical costs for end-to-end (E2E) route management. Quantum Satellite Networks (QSNs) can overcome the limitations of terrestrial optical networks, such as a remarkable signal attenuation over long distances and difficulty of intercontinental communications. The recent studies on quantum satellite communications motivated our research towards a Low Earth Orbit (LEO) quantum satellite backbone for interconnecting quantum on Earth Servers in order to achieve an unprecedented computational capacity. Specifically, our paper proposes a near optimum E2E path evaluation procedure allowing an efficient switching in order to maximize the entanglement generation rate. Indeed, this is one of the main issues that involve the Data Link Layer and the Network Layer of the Quantum Internet (QI) protocol stack, which is in its early standardization phase. In particular, the design of our approach is based on the Software-Defined Networking (SDN) paradigm with the aim of minimizing the number of hops for E2E connection and maximizing network capacity. Therefore, we compare distributed and centralized approaches in order to achieve a trade-off between performance and cost.

Anomaly Detection for Controller Area Networks Using Long Short-Term Memory

The rapid expansion of intra-vehicle networks has increased the number of threats to such networks. Most modern vehicles implement various physical and data-link layer technologies. Vehicles are becoming increasingly autonomous and connected. Controller Area Network (CAN) is one such serial bus system that is used to connect sensors and controllers (Electronic Control Units—ECUs) within a vehicle. ECUs vary widely in processing power, storage, memory, and connectivity. Classical cryptographic approaches are resource intensive. There is a need for efficient security countermeasures for protecting the CAN from various attacks. In this article, we present a novel Long Short-Term Memory (LSTM) network to detect anomalies. Once trained, our system is capable of detecting anomalies in real-time and uses minimal resources. We report the results of our novel prediction algorithm that we use to select optimal LSTM network parameters. Our prediction algorithm and anomaly detection engine have been tested on data from real automobiles. We present the results of our experiments and analyze our findings.

An Advanced Optimization Protocol for Cross Layer Routing in MANET

Through advancements in communication techniques, there have been significant advances in information technology. Information exchange is captive from infrastructure-based to infrastructure-free techniques. Development in wireless technology and portable computing systems has brought interest in the mobile communication field. The increasing flexibility of people around the network has generated demand for mobile networks such as MANET that can be deployed rapidly and without infrastructure. When users of MANET expect effective communication, seamless reliability is currently crucial across heterogeneous mobile wireless systems. The main challenges in adhoc networks are regular topology changes due to flexibility and limited battery capacity for mobile devices. Depletion of the power source may cause early links in the network to be unavailable. Often, due to frequent breaks in path and affects the performance adversely needed for applications as well as node flexibility. This research paper aims to test and suggest a cross-layer interaction model between transport layer, routing layer, data link layer, and physical layer with power-efficient routing intentions. Using the proposed link prediction model, the article modified the incorporated AODV routing protocol by the link prediction algorithm to predict the accessibility time and even before the connection breaks. The proposed algorithm increases the service quality of the network and NS2 simulator checked the model. The simulation results indicate that the performance of the AODV routing algorithm is much more effective than the current algorithm.

Real Time Sensor Data transmission to the IoT Applications using MQTT-SN and MQTT

Internet of Things (IoT) Technology rapidly growing area and active research happening in different Layers of Internet protocol stacks. IOT stack have Physical layer& Data Link layer, Network Layer, Transport layer and Application layer protocols and Applications. Now IOT has many applications like Smart cities, Smart Homes, Environmental monitoring, Agricultural Application and Medical data transmission from remote places to expert Hospital. Numbers of IOT Application Protocols (MQTT, MQTT-SN, COAP, XMPP, and HTPP) are available and implemented in rich resource Environments like good computing power and bandwidth. However all Application protocols are not suitable under lossy wireless sensor network environment. In IOT Environment consists of Sensor Nodes, End Systems and related applications. Latency and bandwidth problems exist between sensor node and End Systems in two tier IOT Environment. To resolve this issue, we proposed Three Tier IOT Architecture; it consists of Sensor Node, IOT Gateway /Fog Computing Node, End Systems and Applications. In this paper we proposed flexible design, development and integration of IOT gateway for different IOT applications using MQTT and MQTT-SN Application Messaging Protocols.

Hybrid Cross Layer Mechanism For High Reliability In Under Water Wireless Sensor Network

Underwater sensor network finds lot of applications in sea environment monitoring. Tsunami like conditions can be monitored and reported earlier so that people on shores can be safe. Due to nature of medium, the data delivery ratio in under water sensor networks is very low. The various problems in the underwater sensor networks are crucial delay, Double side spreading, multipath induced fading, bandwidth limitation, Doppler effects. These problems reduce the data delivery ratio, network lifetime and other parameters.In order to increase the performance of the underwater communication system,Reed Solomon encoding technique with hybrid cross layer methodis used in physical, data link and routing layer . The proposed method increase the reliability of underwater wireless sensor networks.

Minimizing power consumption of LoRa® and LoRaWAN for low-power wireless sensor nodes

In this paper we show that RF transmissions using the physical layer of the “Long Range” (LoRa®) interface, and with some limitations also the data link and network layer Long Range Wide Area Network (LoRaWAN), are suitable even for extremely power-restricted devices, like energy-autonomous wireless sensor nodes (WSNs), if configured well. We analyse the most critical parameters and their influence on the power performance. This includes the outer circuitry, software and configuration of the transmitter SX1276 and the new SX1262. Based on that, we give specific advice to lower their power consumption and verify the impact of these measures with evaluations on an own build low power sensor node.

Classification of DoS Attacks in Smart Underwater Wireless Sensor Network

Due to deployment in sensitive military areas and other security applications, wireless networks are becoming a famous research spot in the field of computer science. To ratify the security and reliability in such kinds of application intrusion detection system can play an important role. There is a need of intrusion detection system, which has the capability to detect a large number of possible threats in wireless sensor networks. This article contains a customized dataset for smart underwater wireless sensor network that can be categorized into four types of DoS attacks (Blackhole, Grayhole, Flooding and Scheduling attacks). For the experimental purpose, since it is highly used in WSN, Low Energy Aware Cluster Hierarchy protocol has been used in this research work. Vector based forwarding provide scalable routing protocol to deploy smart underwater wireless sensor network. Using NS2 network simulator model a scheme has been defined to collect network traffic and create the dataset. Artificial Neural Network has been applied to train the dataset to classify it into different DoS attacks. Experimental work performed here gives high classification rate and accuracy for mentioning attacks with the help of proposed dataset. In future, suggested method can be useful for more attacks like Sybil/Wormhole presented in datalink layer as DoS attacks.

Design of a Reduced SpaceFibre Interface: An Enabling Technology for Low-Cost Spacecraft High-Speed Data-Handling

SpaceFibre is an upcoming on-board high-speed communication protocol for space applications. It has been developed in collaboration with the European Space Agency to answer the growing data-rate requirement of satellite payloads such as Synthetic Aperture Radars or hyper-spectral imagers. SpaceFibre offers a complete set of features (i.e., Fault Detection, Isolation and Recovery, and Quality of Service) that guarantees robust communication at the price of higher complexity. This article proposes an innovative modified implementation of the SpaceFibre standard: R-SpaceFibre. It has been designed to reduce hardware resources while keeping high data-rate capability and flow control. Attention is given to the trade-off between Data link layer complexity reduction and protocol features. The proposed protocol is particularly suitable in scenarios where very low bit error rate is foreseen and data integrity is not critical, for example in imaging instruments. The main advantage is a reduction of more than 40% of logical resources required per single interface. R-SpaceFibre may be a suitable solution for several applications, such as low earth orbit CubeSats, which have strict requirements in terms of available logic resources, mass, volume and cost, and more relaxed constraints in terms of upset immunity.

Tree-Based Intermittent Connection Fault Diagnosis for Controller Area Network

Controller area network (CAN) is the most widely adopted network protocol in vehicle communication systems. The intermittent connection (IC) fault, a random cable connectivity problem with short durations, occurring in the CAN network may result in system performance degradation and system level failures in severe cases. Therefore, the health management of CAN-based networked systems demands effective detection and accurate localization of the IC fault. However, the diagnosis of IC fault in CAN network has not been fully exploited. This paper proposes a novel tree-based IC fault diagnosis method to identify the various IC fault locations in the CAN network. First, the error event pairs for network nodes are defined by analyzing the data-link layer information upon each error. Then, the domains of error event pairs and the information cost of IC faults included in the domains are derived. Finally, a tree-based minimal cost diagnosis algorithm is proposed to find the locations of the IC faults. Laboratory testbed is constructed and the case studies are conducted to demonstrate the performance of the proposed method. The results show that IC fault identified by the proposed method agree well with the case study setups.